1887
3D Electromagnetics
  • ISSN: 2202-0586
  • E-ISSN:

Abstract

In a sedimentary environment, layered models are often capable of reproducing the actual geology more accurately than smooth minimum structure models. We present and evaluate a 2D inversion scheme with lateral constraints (2D-LCI) and sharp boundaries for continuous profile oriented data sets. Here, we focus on resistivity data. All data and models are inverted as one system, producing layered sections with laterally smooth transitions. The models are regularized through laterally equal constraints that tie interface depths and resistivities of adjacent layers. Prior information, originating from e.g. electrical logs, migrates through the lateral constraints to the adjacent models, making resolution of equivalences possible. Information from areas with well resolved parameters will, in a similar way, migrate through the constraints to help resolve the poorly constrained parameters.

The estimated model is complemented by a full sensitivity analysis of the model parameters supporting quantitative evaluation of the inversion result.

For evaluation we use broad-banded von Kármán covariance functions to create various geological realistic models. We compare results from the 2D-LCI routine with results from the widely used smooth minimum structure program Res2dinv. The comparison is point-to-point on resistivities in the model space. The statistics conclude that the 2D-LCI resolves the true models to the same level as Res2dinv.

The clear distinction of separate units and unit boundaries is often critical in hydrogeophysical or geotechnical applications, and hence we suggest using a layered inversion scheme in these cases.

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/content/journals/10.1071/ASEG2003_3DEMab005
2003-04-01
2026-01-20
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References

  1. Auken, E., Foged, N, and Sørensen, K. I., 2002, Model recognition by 1-D laterally constrained inversion of resistivity data: Proceedings - New Technologies and Research Trends Session, 8th meeting EEGS-ES, Aveiro, Portugal, EEGS-ES,
  2. Christiansen, A. V, Auken, E., Sørensen, K. I., and Smith, J. T, 2002, 2-D Laterally Constrained inversion (LCI) of resistivity data: Proceedings - New Technologies and Research Trends Session, 8th meeting EEGS-ES, Aveiro,Portugal, EEGS-ES,
  3. Dahlin, T., 1996, 2D resistivity surveying for environmental and engineering applications, First Break, vol 14, no 7, p 275-283.
  4. Dahlin, T. and Zhou, B., 2002, Gradient and mid-point reffered measurements for multi-channel 2D resistivity imaging: Proceedings, Integrated Case Histories session, 8th meeting EEGS-ES, Aveiro,Portugal,
  5. Dey, A. and Morrison, H. F., 1979, Resistivity Modeling for Arbitrarily Shaped 2-Dimensional Structures: Geophysical Prospecting, 27, 106-136.
  6. Jackson, D. D., 1979, The use of a priori data to resolve non-uniqueness in linear inversion.: Geophys.J.R.astr.Soc, 57, 137-157.
  7. Johansen, H. K., 1977, A Man/Computer Interpretation System for Resistivity Soundings over a Horizontally Stratified Earth: Geophysical Prospecting, 25, 667-691.
  8. Loke, M. H. and Barker, R. D., 1996, Rapid least squares inversion of apparent resistivity pseudosections by a quasi-Newton method: Geophysical Prospecting, 44,131-152.
  9. Loke, M. H., Dahlin, Torleif and Acworth, Ian, 2001, A comparison of smooth and blocky inversion methods in 2-D electrical imaging surveys: 15th Geophysical Conference and Exhibition, August 2001, Brisbane., ASEG,
  10. McGiUivray, P. R., 1992, Forward modeling and inversion of DC resistivity and MMR data: PhD thesis University of British Columbia, Vancouver, Canada
  11. Menke, William. Geophysical Data Analysis - discrete inverse theory. Rev. ed. ø. 1989. San Diego, Academic Press. International Geophysics Series.
  12. Møller, I., Jacobsen, B. H., and Christensen, N. B., 2001, Rapid inversion of 2-D geoelectrical data by multichannel deconvolution: Geophysics, 66, 800-808.
  13. Oldenburg, D. W. and Li.Y, 1994, Inversion of induced polarization data: Geophysics, 59, 1327-1341.
  14. Serban, D. Z. and Jacobsen, B. H., 2001, The use of broadband prioir covariance for inverse palaeoclimate estimation: Geophys.J.Int, 147, 29-40.
  15. Smith, T., Hoversten, M., Gasperikova, E., and Morrison, F., 1999, Sharp boundary inversion of 2D magnetotelluric data: Geophysical Prospecting, 47, 469-486.
  16. Sørensen, K.I., Auken, E., Christensen, N.B., Pellerin, L., 2003, An Integrated Approach for Hydrogeophysical Investigations: New Technologies and a Case History, Accepted for publication in SEG, NSG Vol II: Applications and Case Histories
  17. Tarantola, A. and Valette, B., 1982, Generalized nonlinear inverse problems solved using a least squares criterion: Rewiews of Geophysics and Space Physics, 20, 219-232.
  18. Van Overmeeren, R. A. and Ritsema, I. L., 1988, Continuous vertical electrical sounding: First break, 06, 313-324.
  19. Ward, S. H. and Hohmann, G. W. Electromagnetic theory for geophysical applications. Nabighian, M. N. Electromagnetic methods in applied geophysics. 1[4], 131-311. 1988. Tulsa, Society of exploration geophysicists (SEG).
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  • Article Type: Research Article
Keyword(s): 2D; geoelectric; inversion; stochastic modelling
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